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In recent years, global climate change has had significant biological, temporal, and spatial effects on many terrestrial habitats. The objective of this study was to evaluate the effect of climate change on the geographic distribution of Juniperus excelsa and prioritize its habitats for protection against these effects until 2070. The study was conducted using the MaxEnt species distribution model and two data series GFDL-CM3 and MRI-CGCM3 under scenarios RCP2.6 and RCP4.5 of the 5th IPCC report. Our results revealed that elevation, minimum temperature of coldest month, precipitation of coldest quarter, annual mean temperature, and slope aspect, in that order, have the greatest effects on the species’ distribution in the study area. Under optimistic scenario RCP2.6, both models predicted that the species’ presence area will grow, but under RCP4.5, models predicted that by 2070, some parts of its habitat in western and central heights will be lost because of change in climate parameters like minimum temperature of coldest month and precipitation of coldest quarter. Under the latter scenario, the northeastern parts of the study area showed no changes in terms of climatic parameters and climatic niche. The results of both climate data series indicated that the Juniperus excelsa will slowly migrate to higher elevations to cope with the changing climate. Assessment of the results through field studies showed that outputs of GFDL-CM3 are closer to the reality.

In the present study, the relationship between the distribution of Astragalus verus, climate, soil and topography in Isfahan province was investigated using the CART (Classification and Regression Trees) non-parametric regression. According to the vegetation types dominated by Astragalus verus, 287 sites were selected using stratified-random sampling and 106 presence points were recorded. Non-normally distributed soil variables were normalized according to the skewness type by data transformation. For variables that were not normalized by the data transformation, the inverse distance weighted and for normally distributed variables, kriging methods were used for mapping. To investigate the spatial continuity of these variables, the best variogram was selected. Using the principle component analysis (PCA) and correlation matrix, the most effective factors on distribution were clay percentage, mean temperature of the coldest (Bio11), and driest (Bio9) quarter, minimum temperature of the coldest month (Bio6), annual mean temperature (Bio1), saturated moisture and organic carbon, respectively. Model evaluation using replacement method and using independent data indicated high accuracy of the model. According to the optimum threshold of 0.41 and fuzzy-based habitat suitability map, the suitable habitat for the species was 34.5 % of the area. The results are used in sustainable rangeland management, conservation and their restoration. [ABSTRACT FROM AUTHOR]

Abstract The new-age India has been characterized by the participation of a higher number of women in the labour force. Unfortunately, the issue of sexual harassment in the workplace has also risen. The Sexual Harassment of Women at Workplace (Prevention, Prohibition and Redressal) Act of 2013 is a significant piece of legislation aimed at preventing gender-based discrimination in the workplace. Following the enactment of this law, the University Grants Commission (UGC) issued the UGC (Prevention, Prohibition and Redressal of Sexual Harassment of Women Employees and Students in Higher Educational Institutions) Regulations of 2015. This paper aims to study the existing legal framework for addressing the issue of sexual harassment in India. It analyses the state of implementation of UGC regulations at legal education institutions in Ahmedabad, Gujarat. The study involves a combination of primary and secondary data sourced via the UGC’s online portal and a survey conducted among students at one law school in Ahmedabad. The results show poor compliance with the regulations, and, finally, this paper advocates for a more inclusive and independent grievance redressal mechanism.

• F. ovina is a vulnerable species whose habitat has been severely degraded. • CHAID method showed greater potential in predicting the F. ovina occurrence. • Minimum temperature of coldest month controlled F. ovina occurence. Ferula ovina (Boiss.) is a valuable but vulnerable monocarpic perennial forb species from Apiaceae plant family whose habitat has been degraded over the years; hence identifying the factors controlling its distribution is important to assist range managers for the reclamation activities. The specific objective of this study was to investigate the quantitative relationships between soil properties, topographical features, climate factors and F. ovina distribution in a semiarid part of central Iran and to assess the relative importance of these factors in controlling its spatial variability. To discern these complex relationships, artificial neural networks (ANNs), support vector machines (SVMs), and decision tree CHAID algorithm were employed. Results from the ANN, SVM, and CHAID models indicated that the climate and topographic conditions should be considered more in explaining the variability in F. ovina occurrence and distribution. Factors such as slope, precipitation of warmest month, and minimum temperature of coldest month were identified by the ANN, SVM, and CHAID models as the determinant factors influencing the spatial distribution of F. ovina in central Iran, respectively. Furthermore, CHAID approach showed greater potential in predicting the F. ovina occurrence in the study area. This study provides a strong basis for identifying the most determinant habitat characteristics of F. ovina and other vulnerable or endangered plant species in semiarid rangelands of Iran; however, its general analytical framework could be applied to other parts of the world with similar challenges. [ABSTRACT FROM AUTHOR]

The modeling and mapping of hotspots and coldspots ecosystem services (ESs) is an essential factor in the decision-making process for ESs conservation. Moreover, spatial prioritization is a serious stage in conservation planning. In the present research, based on the InVEST software, Getis-Ord statistics (G i * ), and a set of GIS methods, we quantified and mapped the variation and overlapping among three ESs (carbon storage, soil retention, and habitat quality). Furthermore, an approach was proffered for detecting priority areas to protect multiple ecosystem services. Hotspots recognized via the G i * statistics technique contain a higher capacity for supplying ESs than other areas. This means that protecting these areas with a bigger number of overlapped hotspots can provide more services. Results indicated that population growth accompanied by the increase in construction sites and low-yield agricultural lands in the Zayanderood dam watershed basin has resulted in ES losses. This situation is represented by increasing soil erosion, reduced carbon storage, reduced biodiversity, and fragmented habitat distribution due to land-use change. The statistically significant carbon storage, soil retention, and habitat quality hotspots with above 95% confidence level account for 21.5%, 39.3%, and 16.9% of the study area, respectively. Therefore, a clear framework was presented in this study for setting ES-based conservation priority. Decision makers and land-use planners can also combine this technique into their framework to identify and conserve ES hotspots to support their targeted ecosystem policies., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The biodiversity of an ecosystem is greatly influenced by the spatio-temporal pattern of the landscape. Understanding how landscape type affects habitat quality (HQ) is important for maintaining environmental and ecological sustainability, preserving biodiversity, and guaranteeing ecological health. This research examined the relationship between the HQ and landscape pattern. The study presented an interpretation of the biodiversity variation associated with the landscape pattern in the Zayanderud Dam watershed area by integrating the Land Change Modeler and the InVEST model. Landsat images and maximum likelihood classification were used to analyze the spatio-temporal characteristics of the landscape pattern in 1991 and 2021. The future landscape pattern in 2051 was simulated using a Land Change Modeler. Subsequently, the InVEST model and the landscape maps were used to identify the spatial distribution of HQ and its changes over three periods. The mean values of the HQ in the study area were 0.601, 0.489, and 0.391, respectively, demonstrating a decreasing trend. The effect of landscape pattern change on HQ was also assessed based on landscape metrics, including PD, NP, SHDI, and CONTAG. HQ had a significant positive correlation with the CONTAG parameter (R = 0.78). Additionally, it had a significant inverse correlation with NP (R = - 0.83), PD (R = - 0.61), and SHDI (R = - 0.42). The results showed that the habitats in the northern region had lower quality compared to those in the southern parts of the Zayanderud Dam watershed. The density, diversity, and connectivity of landscape patches significantly influence the HQ in the study area. This research has the potential to enhance understanding of the impacts of land change patterns on biodiversity and establish a scientific basis for the conservation of natural habitats. Additionally, it can facilitate efficient decision-making and planning related to biodiversity conservation and landscape management., (© 2024. The Author(s).)

This study investigated the elicitation effects of several methyl jasmonate (MeJ) concentrations (0, 25, 50, and 100 µM) on various biochemical traits of caraway ( Carum carvi L.) callus cultures. The 25 μM MeJ concentration yielded the highest callus growth rate (0.57 mm day -1 ), total flavonols content (2.58 mg QE g -1 FW) and total carotenoids content (0.04 μg g -1 FW), whereas the highest relative fresh weight (75.72%), total phenolics content (76.90 mg GAE g -1 FW), total flavonoids content (58.49 mg QE g -1 FW) and phenylalanine ammonia lyase activity (3.40 nmol cinnamic acid mg -1 h -1 FW) were obtained with the 50 μM MeJ concentration. The highest antioxidant activity through DPPH assay (8.37%) and malondialdehyde content (7.82 μmol g -1 FW) were observed at 100 μM MeJ. The HPLC conducted 21 days post-elicitation revealed a 5.55-fold increase of carvone accumulation (1.83 μg g -1 DW) at 50 μM MeJ and a 2.7-fold increase (0.62 μg g -1 DW) of limonene at 50 μM MeJ. The optimal dosages applied for carvone and limonene accumulation under MeJ elicitation could be used to scale up the economic production of these elite medicinal compounds through caraway callus cultures.